GE Power: Big Data, Machine learning And ‘The Internet of Energy’

GE Power: Big Data, Machine learning And ‘The Internet of Energy’

The global energy industry is facing disruption as it transitions from fossils to renewables (and occasionally back again). Its challenges include balancing growing demand in developing nations with the need for sustainability, and predicting the effect of extreme weather conditions on supply and demand.

How GE Power uses Big Data in practice

GE Power – whose turbines and generators supply 30 percent of the world’s electricity – has been working on applying Big Data, machine learning and Internet of Things (IoT) technology to build an “internet of energy” to replace the traditional, linear, one-way model of energy delivery.

Ganesh Bell, first and current chief data officer at GE Power, tells me, “If you think about it, the electricity industry is still following a one-hundred-year-old model which our founder, Edison, helped to proliferate. It’s the generation of electrons in one source which are then transmitted in a one-way linear model … That whole infrastructure is now being tested and pushed every day because of the challenges we’re talking about.”

The answer to these challenges, Bell believes, lies in taking advantage of the networked, grid-based generation and delivery infrastructures, while augmenting it with the flow of data. “We think of a world where every electron will have a data bit associated with it, and we associate and track that data and optimise it, and suddenly, from a linear model, we have moved to a networked model,” says Bell. It certainly makes sense in a world where everything is increasingly becoming networked and connected – from the devices in our homes to transport networks.

Functions enabled by advanced analytics and machine learning, such as predictive maintenance and power optimisation, can then be applied to critical infrastructure machinery. As Bell tells me, “We have seen results like reducing unplanned downtime by 5 percent, reducing false positives by 75 percent, reducing operations and maintenance costs by 25 percent – and these start adding up to meaningful value.”

As well as asset performance management, GE categorises its data-powered applications into two other groups – one is operations optimisation, which focuses on insights that can be applied across a whole plant, or enterprise. And the other is business optimisation – applications designed to improve the profitability of customers, “So they can use weather data, energy market pricing data, lots of internal and external data to make sure they are capturing every opportunity for optimising their business and being more profitable.”

Put together, these three categories of application make up the foundations of GE Power’s vision for the “digital power plant” – the first step towards making the internet of energy a possibility.

As an example of GE Power’s need to innovate, it seems increasingly likely that tomorrow’s cars will need a robust and reliable network of energy transmission and charging stations far beyond what is available now. If society is ever going to transition away from petroleum-powered vehicles in meaningful numbers, “smart” energy distribution is needed to make sure power is available to charge our vehicles where and when it’s needed.

The technical details

GE’s transition to data-driven energy distribution is being powered (excuse the pun) by its own Predix platform, billed as its “operating system for the industrial internet.” The platform is behind every part of the analytical process, from the cloud repositories to “edge” analytics – algorithms running on raw sensor or machine data as close as possible to the point it is collected.

Data feeds directly into applications such as GE Power’s own asset performance management software, which enables equipment to be monitored even if it’s from a third-party manufacturer, meaning it covers every machine in a power plant, whether or not it’s manufactured by GE.

Ideas and insights you can steal

Datafication is, along with decentralisation (the move towards generating power close to where it will be used) and decarbonisation (the move away from fossil fuels), one of the three “Ds” disrupting the energy industry. And with that data comes great value.

A recent World Economic Forum report concluded that the power industry will create $1.3 trillion in value over the next 10 years by rolling out IoT ideas such as those put into practice at GE Power. As Bell puts it, “When we start monitoring all these assets and collecting all the data, you unlock huge value – and that’s what we’re truly focused on.”



Written by

Bernard Marr

Bernard Marr is an internationally bestselling author, futurist, keynote speaker, and strategic advisor to companies and governments. He advises and coaches many of the world’s best-known organisations on strategy, digital transformation and business performance. LinkedIn has recently ranked Bernard as one of the top 5 business influencers in the world and the No 1 influencer in the UK. He has authored 16 best-selling books, is a frequent contributor to the World Economic Forum and writes a regular column for Forbes. Every day Bernard actively engages his almost 2 million social media followers and shares content that reaches millions of readers.

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